SoroushVahidi/scidocs huggingface dataset:
Overcoming the Brittleness Bottleneck using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge
(2006)

When humans approach the task of text categorization, they interpret the specific wording of the document in the much larger context of their background knowledge and experience. On the other hand, state-of-the-art information retrieval systems are quite brittle—they traditionally represent documents as bags of words, and are restricted to learning from individual word occurrences in the (necessarily limited) training set. For instance, given the sentence “Wal-Mart supply chain goes real time”, how can a text categorization system know that Wal-Mart manages its stock with RFID technology? And having read that “Ciprofloxacin belongs to the quinolones group”, how on earth can a machine know that the drug mentioned is an antibiotic produced by Bayer? In this paper we present algorithms that can do just that. We propose to enrich document representation through automatic use of a vast compendium of human knowledge—an encyclopedia. We apply machine learning techniques to Wikipedia, the largest encyclopedia to date, which surpasses in scope many conventional encyclopedias and provides a cornucopia of world knowledge. Each Wikipedia article represents a concept, and documents to be categorized are represented in the rich feature space of words and relevant Wikipedia concepts. Empirical results confirm that this knowledge-intensive representation brings text categorization to a qualitatively new level of performance across a diverse collection of datasets.
The Generative Lexicon
(1991)

In this paper, I will discuss four major topics relating to current research in lexical semantics: methodology, descriptive coverage, adequacy of the representation, and the computational usefulness of representations. In addressing these issues, I will discuss what I think are some of the central problems facing the lexical semantics community, and suggest ways of best approaching these issues. Then, I will provide a method for the decomposition of lexical categories and outline a theory of lexical semantics embodying a notion of cocompositionality and type coercion, as well as several levels of semantic description, where the semantic load is spread more evenly throughout the lexicon. I argue that lexical decomposition is possible if it is performed generatively. Rather than assuming a fixed set of primitives, I will assume a fixed number of generative devices that can be seen as constructing semantic expressions. I develop a theory of Qualia Structure, a representation language for lexical items, which renders much lexical ambiguity in the lexicon unnecessary, while still explaining the systematic polysemy that words carry. Finally, I discuss how individual lexical structures can be integrated into the larger lexical knowledge base through a theory of lexical inheritance. This provides us with the necessary principles of global organization for the lexicon, enabling us to fully integrate our natural language lexicon into a conceptual whole.
Centroid-Based Document Classification: Analysis and Experimental Results
(2000)

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intrane ts. Automatic text categorization, which is the task of assigning text documents to pre-specified classes (topics o r themes) of documents, is an important task that can help both in organizing as well as in finding information on these h uge resources. Text categorization presents unique challenges due to the large number of attributes present in t he data set, large number of training samples, and attribute dependencies. In this paper we focus on a simple linear-time centroid-based document classification algorithm, that despite its simplicity and robust performance, has not been extensively studied and analyzed. Our extensive experiments show that this centroid-based classifier consi stently and substantially outperforms other algorithms su ch as Naive Bayesian, k-nearest-neighbors, and C4.5, on a wide range of datasets. O ur analysis shows that the similarity measure used by the centroid-based scheme allows it to class ify new document based on how closely its behavior matches the behavior of the documents belonging to differen t classes, as measured by the average similarity between the documents. This matching allows it to dynamically adjus t for classes with different densities. Furthermore, our analysis shows that the similarity measure of the centroidbased scheme accounts for dependencies between the terms in the different classes. We believe that this feature is the reason why it consistently outperforms other classifiers th at cannot take these dependencies into account.
Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language
(1999)

This article presents a measure of semantic similarity in an is-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their e ectiveness.
Vaginal orgasm is associated with vaginal (not clitoral) sex education, focusing mental attention on vaginal sensations, intercourse duration, and a preference for a longer penis.
(2009)

INTRODUCTION
Evidence was recently provided for vaginal orgasm, orgasm triggered purely by penile-vaginal intercourse (PVI), being associated with better psychological functioning. Common sex education and sexual medicine approaches might undermine vaginal orgasm benefits.


AIMS
To examine the extent to which women's vaginal orgasm consistency is associated with (i) being told in childhood or adolescence that the vagina was the important zone for inducing female orgasm; (ii) how well they focus mentally on vaginal sensations during PVI; (iii) greater PVI duration; and (iv) preference for above-average penis length.


METHODS
  In a representative sample of the Czech population, 1,000 women reported their vaginal orgasm consistency (from never to almost every time; only 21.9% never had a vaginal orgasm), estimates of their typical foreplay and PVI durations, what they were told in childhood and adolescence was the important zone for inducing female orgasm, their degree of focus on vaginal sensations during PVI, and whether they were more likely to orgasm with a longer than average penis.


MAIN OUTCOME MEASURES
The association of vaginal orgasm consistency with the predictors noted above.


RESULTS
Vaginal orgasm consistency was associated with all hypothesized correlates. Multivariate analysis indicated the most important predictors were being educated that the vagina is important for female orgasm, being mentally focused on vaginal sensations during PVI, and in some analyses duration of PVI (but not foreplay) and preferring a longer than average penis.


CONCLUSIONS
Focusing attention on penile-vaginal sensation supports vaginal orgasm and the myriad benefits thereof. Brody S, and Weiss P. Vaginal orgasm is associated with vaginal (not clitoral) sex education, focusing mental attention on vaginal sensations, intercourse duration, and a preference for a longer penis.
Schedulability Analysis for Tasks with Static and Dynamic Offsets
(1998)

In this paper we present an extension to current schedulability analysis techniques for periodic tasks with offsets, scheduled under a preemptive fixed priority scheduler. Previous techniques allowed only static offsets restricted to being smaller than the task periods. With the extension presented in this paper, we eliminate this restriction and we allow both static and dynamic offsets. The most significant application of this extension is in the analysis of multiprocessor and distributed systems. We show that we can achieve a significant increase of the maximum schedulable utilization by using the new technique, as opposed to using previously known worst-case analysis techniques for distributed systems. ___________________ This work has been supported in part by the Comisión Interministerial de Ciencia y Tecnología of the Spanish Government, under grant number TAP97-892
Knowledge Technologies
(2008)

Several technologies are emerging that provide new ways to capture, store, present and use knowledge. This book is the first to provide a comprehensive introduction to five of the most important of these technologies: Knowledge Engineering, Knowledge Based Engineering, Knowledge Webs, Ontologies and Semantic Webs. For each of these, answers are given to a number of key questions (What is it? How does it operate? How is a system developed? What can it be used for? What tools are available? What are the main issues?). The book is aimed at students, researchers and practitioners interested in Knowledge Management, Artificial Intelligence, Design Engineering and Web Technologies. During the 1990s, Nick worked at the University of Nottingham on the application of AI techniques to knowledge management and on various knowledge acquisition projects to develop expert systems for military applications. In 1999, he joined Epistemics where he worked on numerous knowledge projects and helped establish knowledge management programmes at large organisations in the engineering, technology and legal sectors. He is author of the book"Knowledge Acquisition in Practice", which describes a step-by-step procedure for acquiring and implementing expertise. He maintains strong links with leading research organisations working on knowledge technologies, such as knowledge-based engineering, ontologies and semantic technologies.
Hotplug or Ballooning: A Comparative Study on Dynamic Memory Management Techniques for Virtual Machines
(2015)

In virtualization environments, static memory allocation for virtual machines (VMs) can lead to severe service level agreement (SLA) violations or inefficient use of memory. Dynamic memory allocation mechanisms such as ballooning and memory hotplug were proposed to handle the dynamics of memory demands. However, these mechanisms so far have not been quantitatively or comparatively studied. In this paper, we first develop a runtime system called U-tube, which provides a framework to adopt memory hotplug or ballooning for dynamic memory allocation. We then implement fine-grained memory hotplug in Xen. We demonstrate the effectiveness of U-tube for dynamic memory management through two case studies: dynamic memory balancing and memory overcommitment. With these two case studies, we make a quantitative comparison between memory hotplug and ballooning. The experiments show that there is no absolute winner for different scenarios. Our findings can be very useful for practitioners to choose the suitable dynamic memory management techniques in different scenarios.
The big five personality dimensions and entrepreneurial status: a meta-analytical review.
(2006)

In this study, the authors used meta-analytical techniques to examine the relationship between personality and entrepreneurial status. Personality variables used in previous studies were categorized according to the five-factor model of personality. Results indicate significant differences between entrepreneurs and managers on 4 personality dimensions such that entrepreneurs scored higher on Conscientiousness and Openness to Experience and lower on Neuroticism and Agreeableness. No difference was found for Extraversion. Effect sizes for each personality dimension were small, although the multivariate relationship for the full set of personality variables was moderate (R = .37). Considerable heterogeneity existed for all of the personality variables except Agreeableness, suggesting that future research should explore possible moderators of the personality-entrepreneurial status relationship.
A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria
(2018)

People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyze high-volume and high-velocity data streams. This work presents an extensive multidimensional analysis of textual and multimedia content from millions of tweets shared on Twitter during the three disaster events. Specifically, we employ various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields, which exploit different machine learning algorithms to process the data generated during the disaster events. Our study reveals the distributions of various types of useful information that can inform crisis managers and responders as well as facilitate the development of future automated systems for disaster management.
Integral imaging using color multiplexed holographic optical element
(2012)

We propose a novel integral imaging system using holographic optical element (HOE) which can provide multi-color 3-dimensional (3D) images. The optical properties of a lens array are recorded on a photopolymer using color multiplexing method with two different wavelength lasers (473 nm and 532 nm). The lens array HOE recorded on the photopolymer functions as 3D imaging HOE for integral imaging instead of the conventional lens array or concave mirror array. Recording scheme for color multiplexed HOE is presented and the proposed system is experimentally verified.
Gaming frequency and academic performance
(2008)

There are numerous claims that playing computer and video games may be educationally beneficial, but there has been little formal investigation into whether or not the frequency of exposure to such games actually affects academic performance. This paper explores the issue by analysing the relationships between gaming frequency – measured as the amount of time undergraduate students spend playing games in their free time – and their academic performance as measured by their examination marks. Using a sample of 713 students, correlation analyses between gaming frequency and examination performance were conducted for students of varying gaming frequency, study discipline, gender, and general attitudes towards gaming and study. The results reveal that examination marks are in fact negatively correlated with gaming frequency – i.e. frequent gamers generally achieve lower marks than less frequent gamers.
Co-management: concepts and methodological implications.
(2005)

Co-management, or the joint management of the commons, is often formulated in terms of some arrangement of power sharing between the State and a community of resource users. In reality, there often are multiple local interests and multiple government agencies at play, and co-management can hardly be understood as the interaction of a unitary State and a homogeneous community. An approach focusing on the legal aspects of co-management, and emphasizing the formal structure of arrangements (how governance is configured) runs the risk of neglecting the functional side of co-management. An alternative approach is to start from the assumption that co-management is a continuous problem-solving process, rather than a fixed state, involving extensive deliberation, negotiation and joint learning within problem-solving networks. This presumption implies that co-management research should preferably focus on how different management tasks are organized and distributed concentrating on the function, rather than the structure, of the system. Such an approach has the effect of highlighting that power sharing is the result, and not the starting point, of the process. This kind of research approach might employ the steps of (1) defining the social-ecological system under focus; (2) mapping the essential management tasks and problems to be solved; (3) clarifying the participants in the problem-solving processes; (4) analyzing linkages in the system, in particular across levels of organization and across geographical space; (5) evaluating capacity-building needs for enhancing the skills and capabilities of people and institutions at various levels; and (6) prescribing ways to improve policy making and problem-solving.
A model of neuronal responses in visual area MT
(1998)

Electrophysiological studies indicate that neurons in the middle temporal (MT) area of the primate brain are selective for the velocity of visual stimuli. This paper describes a computational model of MT physiology, in which local image velocities are represented via the distribution of MT neuronal responses. The computation is performed in two stages, corresponding to neurons in cortical areas V1 and MT. Each stage computes a weighted linear sum of inputs, followed by rectification and divisive normalization. V1 receptive field weights are designed for orientation and direction selectivity. MT receptive field weights are designed for velocity (both speed and direction) selectivity. The paper includes computational simulations accounting for a wide range of physiological data, and describes experiments that could be used to further test and refine the model.
Text2Scene: Generating Abstract Scenes from Textual Descriptions
(2018)

In this paper, we propose an end-to-end model that learns to interpret natural language describing a scene to generate an abstract pictorial representation. The pictorial representations generated by our model comprise the spatial distribution and attributes of the objects in the described scene. Our model uses a sequence-to-sequence network with a double attentive mechanism and introduces a regularization strategy. These scene representations can be sampled from our model similarly as in languagegeneration models. We show that the proposed model, initially designed to handle the generation of cartoon-like pictorial representations in the Abstract Scenes Dataset, can also handle, under minimal modifications, the generation of semantic layouts corresponding to real images in the COCO dataset. Human evaluations using a visual entailment task show that pictorial representations generated with our full model can entail at least one out of three input visual descriptions 94% of the times, and at least two out of three 62% of the times for each image.
Preference for Nature in Urbanized Societies : Stress , Restoration , and the Pursuit of Sustainability
(2007)

Urbanicity presents a challenge for the pursuit of sustainability. High settlement density may offer some environmental, economic, and social advantages, but it can impose psychological demands that people find excessive. These demands of urban life have stimulated a desire for contact with nature through suburban residence, leading to planning and transportation practices that have profound implications for the pursuit of sustainability. Some might dismiss people’s desire for contact with nature as the result of an anti-urban bias in conjunction with a romantic view of nature. However, research in environmental psychology suggests that people’s desire for contact with nature serves an important adaptive function, namely, psychological restoration. Based on this insight, we offer a perspective on an underlying practical challenge: designing communities that balance settlement density with satisfactory access to nature experience. We discuss research on four issues: how people tend to believe that nature is restorative; how restoration needs and beliefs shape environmental preferences; how well people actually achieve restoration in urban and natural environments; and how contact with nature can promote health. In closing, we consider urban nature as a design option that promotes urban sustainability.
Generation from Abstract Meaning Representation using Tree Transducers
(2016)

Language generation from purely semantic representations is a challenging task. This paper addresses generating English from the Abstract Meaning Representation (AMR), consisting of re-entrant graphs whose nodes are concepts and edges are relations. The new method is trained statistically from AMRannotated English and consists of two major steps: (i) generating an appropriate spanning tree for the AMR, and (ii) applying tree-tostring transducers to generate English. The method relies on discriminative learning and an argument realization model to overcome data sparsity. Initial tests on held-out data show good promise despite the complexity of the task. The system is available open-source as part of JAMR at: http://github.com/jflanigan/jamr
JMASM Algorithms and Code Pseudo-Random Number Generators for Vector Processors and Multicore Processors
(2015)

There is a lack of good pseudo-random number generators capable of utilizing the vector processing capabilities and multiprocessing capabilities of modern computers. A suitable generator must have a feedback path long enough to fit the vector length or permit multiple instances with different parameter sets. The risk that multiple random streams from identical generators have overlapping subsequences can be eliminated by combining two different generators. Combining two generators can also increase randomness by remedying weaknesses caused by the need for mathematical tractability. Larger applications need higher precision. The article discusses hitherto ignored imprecisions caused by quantization errors in the application of generators with prime modulus and when generating uniformly distributed integers with an arbitrary interval length. A C++ software package that overcomes all these problems is offered. The RANVEC1 code combines a Mersenne Twister variant and a multiply-with-carry generator to produce vector output. It is suitable for processors with vector sizes up to 512 bits. Some theorists have argued that there is no theoretical proof that the streams from different generators are statistically independent. The article contends that the request for such a proof misunderstands the nature of the problem, and that the mathematical tractability that would allow such a proof would also defeat it. This calls for a more fundamental philosophical discussion of the status of proofs in relation to deterministic pseudo-random sequences.
Mining Frequent Patterns in Data Streams at Multiple Time Granularities
(2002)

Although frequent-pattern mining has been widely studied and used, it is challenging to extend it to data streams. Compared to mining from a static transaction data set, the streaming case has far more information to track and far greater complexity to manage. Infrequent items can become frequent later on and hence cannot be ignored. The storage structure needs to be dynamically adjusted to reflect the evolution of itemset frequencies over time. In this paper, we propose computing and maintaining all the frequent patterns (which is usually more stable and smaller than the streaming data) and dynamically updating them with the incoming data streams. We extended the framework to mine time-sensitive patterns with approximate support guarantee. We incrementally maintain tilted-time windows for each pattern at multiple time granularities. Interesting
The psychology of globalization.
(2002)

The influence of globalization on psychological functioning is examined. First, descriptions of how globalization is occurring in various world regions are presented. Then the psychological consequences of globalization are described, with a focus on identity issues. Specifically, it is argued that most people worldwide now develop a bicultural identity that combines their local identity with an identity linked to the global culture; that identity confusion may be increasing among young people in non-Western cultures as a result of globalization; that some people join self-selected cultures to maintain an identity that is separate from the global culture; and that a period of emerging adulthood increasingly extends identity explorations beyond adolescence, through the mid- to late twenties.